1.Resistance and Serotype of 152 Strains of Streptococcus pneumoniae
Jing ZHANG ; Ziyong SUN ; Yue MA ; Jingyun LI ; Shaohong JIN
Chinese Journal of Nosocomiology 1994;0(04):-
OBJECTIVE To investigate antibiotic resistance and the prevalence of serotype of Streptococcus pneumoniae in Wuhan.METHODS Totally 152 strains of S.pneumoniae were collected to test the MICs of various antibiotics by agar dilution method according to the approved standard of NCCLS.Serotyping of S.pneumoniae was performed by using quelling reaction.RESULTS Among 152 strains of S.pneumoniae,65(42.76%) strains were resistant to penicillin(MIC≥0.12mg/L).94.08%,50.66%,41.45% and 11.18% of S.pneumoniae were resistant against the first(cefalexin),second(cefaclor) and third(cefaxime and ceftriaxone) generation of cephalosporins respectively.The resistance rates to other antibiotic agents,such as erythromycin,tetracycline,trimethoprim/sulfamethoxazole and chloramphenicol,were 84.21%,88.82%,89.47% and 18.42%,respectively.Strains that were resistant to levofloxacin and moxifloxacin were found both for 1.32%.Twenty serotypes were involved in 152 strains. The prevalent serotypes were 19(25.66%),23(19.08%),6(13.82%),15(7.24%)and 14(4.61%).Eight strains were remained for unable to serotype.All penicillin-resistant S.pneumoniae was included in serotypes 6,19 and 23.CONCLUSIONS The antibiotic resistance of S.pneumoniae is serious in Wuhan.Most of them are multi-resistant strains.Except for fluoroquinolones,ceftriaxone and chloramphenicol, most antibiotic agents have lost there activities against S.pneumoniae.The prevalent serotypes,especially of the multi-resistant strains,were 19,23 and 6.Pneumococcal polyvalent vaccine can well cover these serotypes.
2.Analysis on antimicrobial resistance of clinical bacteria isolated from county hospitals and a teaching hospital.
Ziyong, SUN ; Li, LI ; Xuhui, ZHU ; Yue, MA ; Jingyun, LI ; Zhengyi, SHEN ; Shaohong, JIN
Journal of Huazhong University of Science and Technology (Medical Sciences) 2006;26(3):386-8
The distinction of antimicrobial resistance of clinical bacteria isolated from county hospitals and a teaching hospital was investigated. Disc diffusion test was used to study the antimicrobial resistance of isolates collected from county hospitals and a teaching hospital. The data was analyzed by WHONET5 and SPSS statistic software. A total of 655 strains and 1682 strains were collected from county hospitals and a teaching hospital, respectively, in the year of 2003. The top ten pathogens were Coagulase negative staphylococci (CNS), E. coli, Klebsiella spp., S. areus, P. aeruginosa, Enterococcus spp., Enterobacter spp., otherwise Salmonella spp., Proteus spp., Shigella spp. in county hospitals and Streptococcus spp., Acinetobacter spp., X. maltophilia in the teaching hospital. The prevalence of multi-drug resistant bacteria was 5% (4/86) of methicillin-resistant S. areus (MRSA), 12% (16/133) and 15.8% (9/57) of extended-spectrum beta-lactamases producing strains of E. coli and Klebsiella spp., respectively, in county hospitals. All of the three rates were lower than that in the teaching hospital and the difference was statistically significant (P < 0. 01). However, the incidence of methicillin-resistant CNS (MRCNS) reached to 70% (109/156) in the two classes of hospitals. Generally, the antimicrobial resistant rates in the county hospitals were lower than those in the teaching hospital, except the resistant rates of ciprofloxacin, erythromycin, clindamycin, SMZco which were similar in the two classes of hospitals. There were differences between county hospitals and the teaching hospital in the distribution of clinical isolates and prevalence of antimicrobial resistance. It was the basis of rational use of antimicrobial agents to monitor antimicrobial resistance by each hospital.
3.Role of lumbar subarachnoid continuous drainage in delayed hydrocephalus
Xueguang ZHANG ; Gang CHENG ; Ziyong MA ; Yingying JIAO ; Zhiti ZHANG ; Lei HOU ; Zonglei CHONG
Chinese Journal of Neuromedicine 2015;14(4):516-518
Objective To investigate the treatment effect of lumbar subarachnoid continuous drainage on delayed hydrocephalus in patients with cerebral trauma after decompressive craniectomy.Methods Thirty-two patients with delayed hydrocephalus after decompressive craniectomy,admitted to our hospital from June 2009 to September 2013,were treated by lumbar subarachnoid continuous drainage;and the treatment effect was analyzed.Results After lumbar subarachnoid continuous drainage,14 patients got successful drainage tube being extracted in the first period,5 were in the second cycle;they all got avoidance ofventriculo peritoneal shunt operation.However,the other 13 patients,developed into shunt dependent hydrocephalus,were treated with ventriculoperitoneal shunt operation.No central nervous system infections were noted during the period of draining.Conclusion The treatment of lumbar subarachnoid continuous drainage,with the characteristics of small trauma and easy operating,can reduce the incidence of shunt dependent hydrocephalus,which is developed by delayed hydrocephalus.
4.Mediating effect of insulin related indices on the association between body fat with blood pressure among overweight adults.
Yide YANG ; Yiting YANG ; Lianguo FU ; Shuo WANG ; Renhuai CONG ; Xiaoling WANG ; Zhenghe WANG ; Dongmei MA ; Rui MA ; Ziyong ZOU ; Jun MA
Chinese Journal of Preventive Medicine 2016;50(3):225-229
OBJECTIVETo examine the contribution of insulin related indices on the association between body fat and blood pressure among overweight adults.
METHODSFrom April to May 2014, based on convenience sampling, we recruited overweight and obese volunteer participants aged 20-55 years living in Beijing at least 1 year through a strict examination by doctors in a physical examination center. In this study, we excluded the participants who reported suffering from any severe heart, lung, liver or kidney organic diseases, and abnormal development, disabilities, and secondary obesity caused by other disease. Also participants with use of antihypertensive drugs, hypoglycemic drugs and lipid lowering drugs were excluded for this study. A total of 1 221 participants were investigated in this study. With a simple self-designed questionnaire, the birthdates, sex, drug use, and disease history were examined. Participants' blood pressure (BP), percentage of body fat (PBF), glucose and fasting insulin level were measured. Mediation analysis was used to analyze the total effect of PBF on BP (c), the association between PBF and insulin related indices (a), and the mediation effect of serum fasting insulin level/HOMA-IR/HOMA-%S on relation between PBF and systolic/diastolic blood pressure (SBP/DBP).
RESULTSPBF was positively associated with SBP (c=0.25 ± 0.05 and 0.19 ± 0.03 for male and female, respectively, P<0.001). In males, PBF was positively associated with fasting insulin level and HOMA-IR (a=0.28 ± 0.05 and 0.24 ± 0.05, P<0.001), and negatively associated with HOMA-%S (a=-0.29 ± 0.05, P<0.001); in females, PBF was positively associated with fasting insulin level, HOMA-IR (a=0.21 ± 0.04 and 0.20 ± 0.04, P<0.001), and negatively associated with HOMA-%S (a=-0.13 ± 0.04, P<0.001). In further mediation analysis for female participants, fasting insulin level/HOMA-IR/HOMA-%S played mediation roles in the relation between PBF and SBP, with ratio of mediation of 13.78%,18.3%, and 5.98%. Fasting insulin level/HOMA-IR also mediated the relation between PBF and DBP, with mediation ratio of 11.98% and 14.13%.
CONCLUSIONIn overweight/obese female participants, insulin related indices mediated the relation between PBF and BP.
Adipose Tissue ; physiology ; Adult ; Beijing ; Blood Glucose ; analysis ; Blood Pressure ; Body Mass Index ; Female ; Humans ; Insulin ; physiology ; Insulin Resistance ; Male ; Middle Aged ; Obesity ; physiopathology ; Overweight ; physiopathology ; Risk Factors ; Young Adult
5.Analysis on Antimicrobial Resistance of Clinical Bacteria Isolated from County Hospitals and a Teaching Hospital
Ziyong SUN ; Li LI ; Xuhui ZHU ; Yue MA ; Jingyun LI ; Zhengyi SHEN ; Shaohong JIN
Journal of Huazhong University of Science and Technology (Medical Sciences) 2006;26(3):386-388
The distinction of antimicrobial resistance of clinical bacteria isolated from county hospitals and a teaching hospital was investigated. Disc diffusion test was used to study the antimicrobial resistance of isolates collected from county hospitals and a teaching hospital. The data was analyzed by WHONET5 and SPSS statistic software. A total of 655 strains and 1682 strains were collected from county hospitals and a teaching hospital, respectively, in the year of 2003. The top ten pathogens were Coagulase negative staphylococci (CNS), E. coli, Klebsiella spp. , S. areus, P. aeruginosa, Enterococcus spp. , Enterobacter spp. , otherwise Salmonella spp. , Proteus spp. , Shigella spp. in county hospitals and Streptococcus spp. , Acinetobacter spp. , X. maltophilia in the teaching hospital. The prevalence of multi-drug resistant bacteria was 5% (4/86) of methicillin-resistant S. areus (MRSA), 12% (16/133) and 15.8 % (9/57) of extended-spectrum β-lactamases producing strains of E. coli and Klebsiella spp. , respectively, in county hospitals. All of the three rates were lower than that in the teaching hospital and the difference was statistically significant (P<0.01). However, the incidence of methicillin-resistant CNS (MRCNS) reached to 70 % (109/156) in the two classes of hospitals. Generally, the antimicrobial resistant rates in the county hospitals were lower than those in the teaching hospital, except the resistant rates of ciprofloxacin, erythromycin, clindamycin, SMZco which were similar in the two classes of hospitals. There were differences between county hospitals and the teaching hospital in the distribution of clinical isolates and prevalence of antimicrobial resistance. It was the basis of rational use of antimicrobial agents to monitor antimicrobial resistance by each hospital.
6.COVID-ONE-hi:The One-stop Database for COVID-19-specific Humoral Immunity and Clinical Parameters
Xu ZHAOWEI ; Li YANG ; Lei QING ; Huang LIKUN ; Lai DAN-YUN ; Guo SHU-JUAN ; Jiang HE-WEI ; Hou HONGYAN ; Zheng YUN-XIAO ; Wang XUE-NING ; Wu JIAOXIANG ; Ma MING-LIANG ; Zhang BO ; Chen HONG ; Yu CAIZHENG ; Xue JUN-BIAO ; Zhang HAI-NAN ; Qi HUAN ; Yu SIQI ; Lin MINGXI ; Zhang YANDI ; Lin XIAOSONG ; Yao ZONGJIE ; Sheng HUIMING ; Sun ZIYONG ; Wang FENG ; Fan XIONGLIN ; Tao SHENG-CE
Genomics, Proteomics & Bioinformatics 2021;19(5):669-678
Coronavirus disease 2019(COVID-19),which is caused by SARS-CoV-2,varies with regard to symptoms and mortality rates among populations.Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19.However,differences in immune responses and clinical features among COVID-19 patients remain largely unknown.Here,we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters(named COVID-ONE-hi).COVID-ONE-hi is based on the data that contain the IgG/IgM responses to 24 full-length/truncated proteins corresponding to 20 of 28 known SARS-CoV-2 proteins and 199 spike protein peptides against 2360 serum samples collected from 783 COVID-19 patients.In addition,96 clinical parameters for the 2360 serum samples and basic information for the 783 patients are integrated into the database.Furthermore,COVID-ONE-hi provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups.A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters.After the"START"button is clicked,one can readily obtain a comprehensive analysis report for further interpretation.COVID-ONE-hi is freely available at www.COVID-ONE.cn.
7.Antimicrobial resistance profile of clinical isolates in hospitals across China: report from the CHINET Surveillance Program, 2017
Fupin HU ; Yan GUO ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; Yuanhong XU ; Jilu SHEN ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Dawen GUO ; Jinying ZHAO ; Wenen LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Kaizhen WEN ; Yirong ZHANG ; Xuesong XU ; Chao YAN ; Hua YU ; Xiangning HUANG ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Hongyan ZHENG ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2018;18(3):241-251
Objective To investigate the antimicrobial resistance profile of the clinical isolates collected from selected hospitals across China. Methods Twenty-nine general hospitals and five children's hospitals were involved in this program. Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems. Results were interpreted according to CLSI 2017 breakpoints. Results A total of 190 610 clinical isolates were collected from January to December 2017, of which gram negative organisms accounted for 70.8% (134 951/190 610) and gram positive cocci 29.2% (55 649/190 610). The prevalence of methicillin-resistant strains was 35.3% in S. aureus (MRSA) and 80.3% in coagulase negative Staphylococcus (MRCNS) on average. MR strains showed much higher resistance rates to most of the other antimicrobial agents than MS strains. However, 91.6% of MRSA strains were still susceptible to trimethoprim-sulfamethoxazole, while 86.2% of MRCNS strains were susceptible to rifampin. No staphylococcal strains were found resistant to vancomycin. E. faecalis strains showed much lower resistance rates to most of the drugs tested (except chloramphenicol) than E. faecium. Vancomycin-resistant Enterococcus (VRE) was identified in both E. faecalis and E. faecium. The identified VRE strains were mainly vanA, vanB or vanM type based on phenotype or genotype. The proportion of PSSP or PRSP strains in the non-meningitis S.pneumoniae strains isolated from children decreased but the proportion of PISP strains increased when compared to the data of 2016. Enterobacteriaceae strains were still highly susceptible to carbapenems. Overall, less than 10% of these strains (excluding Klebsiella spp.) were resistant to carbapenems. The prevalence of imipenem-resistant K. pneumoniae increased from 3.0% in 2005 to 20.9% in 2017, and meropenem-resistant K. pneumoniae increased from 2.9% in 2005 to 24.0% in 2017, more than 8-fold increase. About 66.7% and 69.3% of Acinetobacter (A. baumannii accounts for 91.5%) strains were resistant to imipenem and meropenem, respectively. Compared with the data of year 2016, P. aeruginosa strains showed decreasing resistance rate to carbapenems. Conclusions Bacterial resistance is still on the rise. It is necessary to strengthen hospital infection control and stewardship of antimicrobial agents. The communication between laboratorians and clinicians should be further improved in addition to surveillance of bacterial resistance.
8.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
9.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
10.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.